1. Field
The present invention relates to wireless communication systems, and more particularly to wireless communication systems having multiple-input, multiple-output (MIMO) capability, especially but not exclusively Orthogonal Frequency Division Multiple Access (OFDMA) systems including those compliant with the LTE (Long Term Evolution) and LTE-A groups of standards.
2. Description of the Related Art
Wireless communication systems are widely known in which a base station (BS) communicates with multiple subscriber stations (SS or MS, also called users) within range of the BS. The area covered by one BS is called a cell and typically, many base stations are provided in appropriate locations so as to cover a wide geographical area more or less seamlessly with adjacent cells. Each BS divides its available bandwidth, i.e. frequency and time resources, into individual resource allocations for the users. There is a constant need to increase the capacity of such systems in order to accommodate more users and/or more data-intensive services.
OFDM (Orthogonal Frequency Division Multiplex) is one known technique for transmitting data in a wireless communication system. An OFDM based communications scheme divides data symbols to be transmitted among a large number of subcarriers (also called frequency fingers) which are equally spaced in frequency, hence frequency division multiplexing. By carrying only a small amount of data on each subcarrier, the bit rate per subcarrier is kept low and hence intersymbol interference is reduced. Data is modulated onto a subcarrier by adjusting its phase, amplitude, or both phase and amplitude.
The “orthogonal” part of the name OFDM refers to the fact that the spacings of the subcarriers are specially chosen so as to be orthogonal, in a mathematical sense, to the other subcarriers. More precisely, they are arranged along the frequency axis such that the sidebands of adjacent subcarriers are allowed to overlap but can still be received without inter-subcarrier interference, commonly referred to as ICI. In mathematical terms, the sinusoidal waveforms of each subcarrier are called eigenfunctions of a linear channel, with the peak of each sinusoid coinciding with a null of every other sinusoid. This can be achieved by making the subcarrier spacing a multiple of the reciprocal of the symbol period.
When individual subcarriers or sets of subcarriers are assigned to different users of the wireless communication system, the result is a multi-access system referred to as OFDMA. (In this specification, the term OFDM is henceforth used to include OFDMA). By assigning distinct frequency/time resources to each user in a cell, OFDMA can substantially avoid interference among the users within a cell. However, interference from adjacent cells can still be a problem as explained later.
A further modification of the basic OFDM scheme is called MIMO OFDM, where MIMO stands for multiple-input multiple-output. This scheme employs multiple antennas (or antenna ports, see below) at both the transmitter and the receiver to enhance the data capacity achievable between the BS and each user. For example, a 4×4 MIMO channel is one in which transmitter and receiver communicate with one another each using four antennas. There is no need for the transmitter and receiver to employ the same number of antennas. Typically, a base station in a wireless communication system will be equipped with many more antennas in comparison with a mobile handset, owing to differences in power, cost and size limitations.
Considering the simplest example of a transmitter (e.g. base station) communicating with a single receiver (subscriber station), the MIMO channel is the frequency (or equivalently time delay) response of the radio link between the transmitter and receiver. It contains all the sub-carriers, and covers the whole bandwidth of transmission. A MIMO channel contains many individual radio links, hence it has Nt×Nr SISO (Single-Input Single-Output) channels (also called sub-channels). For example, a 2×2 MIMO arrangement contains 4 links and hence 4 SISO channels. The SISO channels can be combined in various ways to transmit one or more data streams to the receiver.
FIG. 1 is a conceptual diagram of a generalized MIMO system. In FIG. 1, a transmitter transmits signals utilizing Nt transmitting antennas, and the receiver receives the signals from the transmitter utilizing Nr receiving antennas. The characteristics of the individual SISO channels or subchannels between the transmitter and receiver are denoted by H0,0 to HNr-1, Nt-1, and as indicated in the Figure, these form terms of a matrix called the channel matrix or channel response matrix H. “H0,0” indicates the channel characteristics (for example, channel frequency response) for transmitting signals from the transmitting antenna 0 to the receiving antenna 0. “HNr-1, Nt-1” indicates the channel characteristics for transmitting signals from the transmitting antenna Nt−1 to the receiving antenna Nr−1, and so on. Since the receiving antennas are not individually addressable by the transmitter, there are a maximum of Nt data streams. The channel can be assumed to remain approximately the same (more or less unchanged in its properties) for a certain length of time called the channel coherence time.
In FIG. 1, the symbols x0 to xNt-1 which are transmitted using the transmitting antennas N0 to NNt-1, form a transmit vector x. Likewise, received signals y0 to yNr-1, which are received using the receiving antennas N0 to NNr-1, together form a received signal vector y. Without precoding (see below), the vectors y and x are related by:y=Hx+n  (1)where H is the channel matrix and n is a term representing noise in each receiving antenna.
The channel matrix H has a “rank” which is the number of independent rows or columns, which in practical terms means the number of independent signals capable of being transmitted from the antenna ports. When some of the rows or columns are mutually-dependent (indicating correlation between the individual subchannels) the MIMO channel is called “rank deficient”. In such a case, the MIMO channel is incapable of providing the maximum data throughput due to correlation.
MIMO transmission schemes include so-called non-adaptive and adaptive configurations. In the non-adaptive case, the transmitter does not have any knowledge of the channel properties and this limits performance, as the transmitter cannot take account of changes in conditions (channel profile). Adaptive schemes rely on the receiver feeding back information (channel-state information or CSI) to the transmitter, or locally deriving the CSI, allowing it to adapt the transmitted signal to changing conditions and maximize data throughput. A feedback path (not shown) from the receiver to the transmitter carries the feedback signals for informing the transmitter of the channel properties.
Closed loop systems are required in FDD (Frequency Division Duplex) systems, where the uplink (mobile to base station) and downlink (vice-versa) employ two different carrier frequencies. Because of the frequency change, the uplink and downlink channels are different and CSI needs to be fed back. In TDD (Time Division Duplex) systems—also referred to simply as TD (Time Division)—the uplink and downlink are transmitted in two adjacent time slots on the same frequency. The two time slots are within the channel coherence time (the channel does not change) so the channel state information need not be fed back. The transmitter can estimate the channel from the received signal on the reverse link, usually aided by the insertion of pilots or known waveforms by the transmitter into the signal sent on the reverse link.
The invention to be described is mainly applicable to TDD systems, and to the downlink, namely transmissions from a base station acting as the transmitter to its users acting as receivers, rather than with the uplink.
Typically, MIMO configurations involve pre-coding at the transmitter, whereby the data symbols to be transmitted are weighted using eigenvectors of each subcarrier, subchannel or subchannel group. In other words, channel-state information is used to adapt the transmit vector x to the channel conditions. This effectively allows the MIMO channel to be decomposed into a set of parallel SISO channels, so-called eigenmode signaling, so that the symbols are (given perfect channel-state information) perfectly separated at the receiver. The eigenmodes available in the channel are also called spatial modes.
Since the radio channel from eNB (evolved Node B) to UE (User Equipment) varies over time, space and frequency, the transmission from the eNB can be received with higher quality if it is ‘precoded’ prior to transmission. This modifies equation (1) as follows, where P is the precoder used at a particular time-frequency index:y=HPx+n  (2)
In equation (2), the data streams are represented by x, which is equivalent to the minimum number of transmit and receive antenna ports. For example, in a system with 4Tx and 2Rx antenna ports, x=2. Even if x is 1 (1×1 vector), the pre-coder P can be 2×1 vector, making Px a 2×1 vector. Hence there are two transmit streams, feeding two transmit antennas, and this can be considered spatial multiplexing even in the case of a single data stream.
Precoding can be either linear, achieving reasonable results whilst limiting the complexity of processing, or non-linear, achieving near-optimal results but at the cost of greater complexity. One form of linear precoding, employed in the invention to be described, is so-called “zero-forcing” as described below.
In an ideal case, precoder P is selected such as to satisfy P=V*, where * denotes the Hermitian transpose, in the singular value decomposition (SVD) of H:H=UΣV  (3)with the matrices following the usual SVD definitions.
FIG. 2 is a diagram showing the configuration of a MIMO system in more concrete terms. MIMO system 1 comprises a transmitter 2 which comprises a plurality of transmitting antennas and a receiver 3 which comprises a plurality of receiving antennas.
The transmitter 2 transmits symbols 0 to Nt−1 in parallel using Nt transmitting antennas; the symbols can be created from one data stream, referred to as vertical encoding, or different data streams, referred to as horizontal encoding. In addition, each transmitted symbol corresponds to, for example, one-bit data if the modulation method is BPSK, and corresponds to two-bit data if the modulation method is QPSK. The receiver 3 receives the signals transmitted from the transmitting device 2 using Nr receiving antennas, and it comprises a signal regeneration unit 4 which regenerates the transmitted symbols from the signals received. In this configuration, a number of spatial modes is available corresponding to the minimum value of Nt and Nr.
As indicated by the arrows in FIG. 2, the signals transmitted from each of the plurality of transmitting antennas are received by each of the plurality of receiving antennas, giving rise to Nt×Nr subchannels in total. In other words, the signals transmitted from the transmitting antenna (0) are received by receiving antennas (0) through (Nr−1), and likewise, the signals transmitted from the transmitting antennas (Nt−1) are also received by the receiving antennas (0) through (Nr−1). The characteristics of the subchannel which propagates the signals from the i-th transmitting antenna to the j-th receiving antenna are expressed as “Hij” and form one component term of the Nt×Nr channel matrix H.
The subchannel characteristics are measured prior to transmission of actual data, typically by sending pilot (or reference) signals. The transmitter 2 first transmits a pilot signal using the transmitting antenna (0). The receiver 3 receives the pilot signal transmitted from the transmitting antenna (0) through the receiving antennas (0) to (Nr−1). In this case, since the transmitting power of the pilot signal is determined in advance, the receiving device 3 obtains each component (H0,0 to H0,Nr-1) of the first row in the channel matrix by monitoring the power, SNR, etc. of the signal received through the receiving antennas (0) to (Nr−1). Thereafter, each component of the 2nd to Nt-th rows in the channel matrix can be obtained, in the same way using pilot signals transmitted from each transmitting antenna.
In the MIMO system 1, if the symbol x (x0˜xNt-1) is transmitted from the transmitting device 2, the signal y (y0˜yNr-1) detected in the receiving device 3 is expressed by equation (2). Therefore, in the absence of noise n, the receiving device 3 can obtain correct transmitted symbols by detecting the channel matrix H and performing an inverse operation corresponding to the influence of each component in the channel matrix H on the signal. In practice, however, noise n is present and in addition, the channel matrix H cannot be determined with absolute accuracy. Therefore, the receiver 3 estimates the transmitted symbol from the received signal y and the channel matrix H and introduces an algorithm for minimizing the error of this estimated value.
By way of background explanation, a MIMO-OFDM transmitter and receiver will be briefly outlined with reference to FIGS. 3 and 4. FIG. 3 is a schematic diagram of a MIMO-OFDM transmitter. High-speed binary data is encoded (convolutional code is an example), interleaved, and modulated (using a modulation scheme such as BPSK, QPSK, 64QAM, and the like). Independent channel encoders may be used for each transmitting antenna. Subsequently, the data is converted into parallel low-speed modulated data streams which are fed to N sub-carriers. The output from each encoder is carried separately on a plurality of sub-carriers. The modulated signals are individually pre-coded and then frequency-division multiplexed by N-point inverse fast Fourier transform (IFFT) The resulting OFDM signal is converted into an analog signal by a D/A converter, is upconverted into the RF band, and transmitted over the air.
At the MIMO-OFDM receiver schematically shown in FIG. 4, the received signals from the Nr receive antennas are filtered by a band pass filter (BPF), not shown, and then down-converted to a lower frequency. The down-converted signal from each antenna is sampled by an A/D converter, not shown, to convert it into a digital signal, and the guard interval is removed as denoted by “-GI” in the Figure. Then, the sampled data is fed to the N-point fast Fourier transformer (FFT). After Fourier transformation is performed on each of the signals received through the Nr receive antennas, they are fed to the MIMO signal processing unit 11. Here, the MIMO signal processing unit 11 comprises a signal regeneration unit 4 which performs algorithms to compensate for the channel characteristics, using the channel matrix H and taking account of the precoding applied on the transmitter side. In this example, the output of the MIMO signal processing unit 11 is Nt independent data streams, and each data stream is independently demodulated, de-interleaved, and decoded. However, the outputs may be demultiplexed to form a single data stream, if a single stream was multiplexed, i.e. vertical encoding was applied, at the transmitter on to multiple antennas.
The above explanation has considered the case of a single transmitter sending MIMO signals to a single receiver, but of course a practical MIMO wireless communication system is much more elaborate than this, providing many mutually-adjacent cells in each of which a base station transmits over respective MIMO channels to multiple subscriber stations simultaneously. In practice, the adjacent cells overlap to some extent such that transmissions from one base station in one cell can cause interference to users at the edges of adjacent cells. If the cells have a hexagonal grid arrangement, then one cell may be adjacent to up to six neighboring cells such that transmissions to a particular user may cause interference in more than one other cell.
MIMO and OFDMA are expected to enable high-capacity data throughput in future wireless communication systems such as those compliant with LTE-Advanced (below, LTE-A), or IEEE802.16m (also called Advanced WiMAX (Worldwide Interoperability for Microwave Access) or Gigabit WiMAX). However, the above multi-user interference effects can become a significant obstacle in achieving the expected capacity enhancements in such systems. For example, a user near the edge of one cell, communicating with one BS using a particular frequency/time resource, may interfere with a user in an adjacent cell, served by a different BS using the same frequency/time resource.
Consequently, in OFDMA based LTE wireless cellular systems, intercell interference, particularly at the cell edges, can be a significant obstacle in providing a high quality of service. Known techniques to mitigate inter-cell interference include Inter-Cell Interference Coordination (ICIC), and enhanced Inter-Cell Interference Coordination (eICIC). Briefly, these schemes work on avoiding the same time frequency resources being used in adjacent cells by eNB coordination, and distinguish between resources which could be used at cell centre and resources which could be used at cell edge.
However when the cells become fully loaded (because LTE supports a frequency reuse of 1, to enable higher throughputs), it becomes very difficult to avoid interference in the above manner. This problem is aggravated if the signals from supposedly cell centre regions spill over to the cell edges. Such situations can occur for example in street canyons in outdoor networks and in corridors in indoor networks. In such cases some form of interference cancellation is required to provide a good enough service to the cell edge user. There is consequently a need to implement a MIMO pre-coding scheme, which can improve the quality of service to the cell edge users. A scenario of particular relevance is where the loading of the two cells is such that schedulers cannot allocate resource blocks to UEs which result in sufficiently low interference to allow acceptable performance, implying that the existing time and frequency domain techniques may not be good enough on their own.
A MIMO pre-coding based interference cancellation scheme applicable in Rel.8, 9 of the LTE-FDD standards was proposed in the applicant's co-pending European Patent Application No. 12187490.3, based on codebook based PMI feedback. However, in a codebook based PMI method, the choices of precoding vector P are finite and hence it will be only an approximate fit to the channel H.
The following LTE standards documents provide background information and are hereby incorporated by reference:
3GPP TS36.213, v.10.5.0
3GPP TS36.211, v.10.4.0.